org.nd4j.linalg.factory.Nd4j.concat()方法的使用及代码示例

x33g5p2x  于2022-01-24 转载在 其他  
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本文整理了Java中org.nd4j.linalg.factory.Nd4j.concat()方法的一些代码示例，展示了Nd4j.concat()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Nd4j.concat()方法的具体详情如下：
包路径：org.nd4j.linalg.factory.Nd4j
类名称：Nd4j
方法名：concat

Nd4j.concat介绍

[英]Concatneate ndarrays along a dimension
[中]沿着一个维度连续排列

代码示例

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Concatenates two matrices horizontally.
  3.  * Matrices must have identical
  4.  * numbers of rows.
  5.  *
  6.  * @param arrs
  7.  */
  8. public INDArray hstack(INDArray... arrs) {
  9.   return Nd4j.concat(1, arrs);
  10. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Concatenates two matrices vertically. Matrices must have identical
  3.  * numbers of columns.
  4.  *
  5.  * @param arrs
  6.  */
  7. @Override
  8. public INDArray vstack(final INDArray... arrs) {
  9.   return Nd4j.concat(0, arrs);
  10. }

代码示例来源：origin: deeplearning4j/dl4j-examples

  1. static INDArray append(INDArray arr1, INDArray values, int dimension) {
  2.   if(dimension == -1) {
  3.     return Nd4j.toFlattened(arr1, values);
  4.   } else {
  5.     return Nd4j.concat(dimension, arr1, values);
  6.   }
  7. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Get a view of the underlying array
  3.  * relative to the size of the actual array.
  4.  * (Sometimes there are overflows in the internals
  5.  * but you want to use the internal INDArray for computing something
  6.  * directly, this gives you the relevant subset that reflects the content of the list)
  7.  * @return the view of the underlying ndarray relative to the collection's real size
  8.  */
  9. public INDArray array() {
  10.   List<INDArray> retList = new ArrayList<>(list.size());
  11.   for(X x : list) {
  12.     retList.add(x.array());
  13.   }
  14.   return Nd4j.concat(0,retList.toArray(new INDArray[retList.size()]));
  15. }

代码示例来源：origin: deeplearning4j/dl4j-examples

  1. System.out.println(ones);
  2. INDArray combined = Nd4j.concat(0,zeros,ones);
  3. INDArray combined2 = Nd4j.concat(1,zeros,ones);

代码示例来源：origin: deeplearning4j/nd4j

  1. return Nd4j.concat(0,resultList.toArray(new INDArray[resultList.size()]));

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Append the given
  3.  * array with the specified value size
  4.  * along a particular axis
  5.  * @param arr the array to append to
  6.  * @param padAmount the pad amount of the array to be returned
  7.  * @param val the value to append
  8.  * @param axis the axis to append to
  9.  * @return the newly created array
  10.  */
  11. public static INDArray append(INDArray arr, int padAmount, double val, int axis) {
  12.   if (padAmount == 0)
  13.     return arr;
  14.   long[] paShape = ArrayUtil.copy(arr.shape());
  15.   if (axis < 0)
  16.     axis = axis + arr.shape().length;
  17.   paShape[axis] = padAmount;
  18.   INDArray concatArray = Nd4j.valueArrayOf(paShape, val);
  19.   return Nd4j.concat(axis, arr, concatArray);
  20. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Append the given
  3.  * array with the specified value size
  4.  * along a particular axis
  5.  * @param arr the array to append to
  6.  * @param padAmount the pad amount of the array to be returned
  7.  * @param val the value to append
  8.  * @param axis the axis to append to
  9.  * @return the newly created array
  10.  */
  11. public static INDArray prepend(INDArray arr, int padAmount, double val, int axis) {
  12.   if (padAmount == 0)
  13.     return arr;
  14.   long[] paShape = ArrayUtil.copy(arr.shape());
  15.   if (axis < 0)
  16.     axis = axis + arr.shape().length;
  17.   paShape[axis] = padAmount;
  18.   INDArray concatArr = Nd4j.valueArrayOf(paShape, val);
  19.   return Nd4j.concat(axis, concatArr, arr);
  20. }

代码示例来源：origin: deeplearning4j/nd4j

  1. return Nd4j.concat(0,arrList.toArray(new INDArray[arrList.size()]));

代码示例来源：origin: deeplearning4j/nd4j

  1. return Nd4j.concat(0,arrList.toArray(new INDArray[arrList.size()]));

代码示例来源：origin: deeplearning4j/dl4j-examples

  1. static INDArray insert(INDArray arr1, int index, INDArray values, int dimension) {
  2.   if(dimension == -1) {
  3.     INDArray flat1 = Nd4j.toFlattened(arr1);
  4.     INDArray flatValues = Nd4j.toFlattened(values);
  5.     INDArray firstSlice = flat1.get(NDArrayIndex.interval(0, index));
  6.     INDArray secondSlice = flat1.get(NDArrayIndex.interval(index, flat1.length()));
  7.     return Nd4j.toFlattened(firstSlice, flatValues, secondSlice);
  8.   } else {
  9.     INDArray firstSlice = arr1.get(createIntervalOnDimension(dimension, false,
  10.       0, index));
  11.     INDArray secondSlice = arr1.get(createIntervalOnDimension(dimension, false,
  12.       index, arr1.shape()[dimension]));
  13.     return Nd4j.concat(dimension, firstSlice, values, secondSlice);
  14.   }
  15. }

代码示例来源：origin: deeplearning4j/dl4j-examples

  1. static INDArray delete(int dimension, INDArray arr1, int... interval) {
  2.   int length = interval.length;
  3.   int lastIntervalValue = interval[length - 1];
  4.   if(dimension == -1) {
  5.     INDArray array1 = arr1.get(NDArrayIndex.interval(0, interval[0]));
  6.     if(lastIntervalValue == arr1.length() - 1) {
  7.       return Nd4j.toFlattened(array1);
  8.     } else {
  9.       INDArray array2 = arr1.get(NDArrayIndex.interval(lastIntervalValue + 1,
  10.         arr1.length()));
  11.       return Nd4j.toFlattened(array1, array2);
  12.     }
  13.   } else {
  14.     INDArray array1 = arr1.get(createIntervalOnDimension(dimension, false, 0, interval[0]));
  15.     if(lastIntervalValue == arr1.shape()[dimension] - 1) {
  16.       return array1;
  17.     } else {
  18.       INDArray array2 = arr1.get(createIntervalOnDimension(dimension, false,
  19.         lastIntervalValue + 1,
  20.         arr1.shape()[dimension]));
  21.       return Nd4j.concat(dimension, array1, array2);
  22.     }
  23.   }
  24. }

代码示例来源：origin: deeplearning4j/dl4j-examples

  1. INDArray concatenatedAxisZero = Nd4j.concat(0, Nd4j.create(3, 2), Nd4j.create(5, 2));
  2. print("Concatenated arrays on dimension zero", concatenatedAxisZero);
  3. INDArray concatenatedAxisOne = Nd4j.concat(1, Nd4j.create(3, 2), Nd4j.create(3, 5));
  4. print("Concatenated arrays on dimension 1", concatenatedAxisOne);

代码示例来源：origin: org.nd4j/nd4j-api

  1. /**
  2.  * Concatenates two matrices horizontally.
  3.  * Matrices must have identical
  4.  * numbers of rows.
  5.  *
  6.  * @param arrs
  7.  */
  8. public INDArray hstack(INDArray... arrs) {
  9.   return Nd4j.concat(1, arrs);
  10. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. /**
  2.  * Concatenates two matrices vertically. Matrices must have identical
  3.  * numbers of columns.
  4.  *
  5.  * @param arrs
  6.  */
  7. @Override
  8. public INDArray vstack(final INDArray... arrs) {
  9.   return Nd4j.concat(0, arrs);
  10. }

代码示例来源：origin: neo4j-graph-analytics/ml-models

  1. private void diffuse(List<Pruning.Feature> featuresList) {
  2.   INDArray ndDiffused = Nd4j.create(embedding.shape());
  3.   Nd4j.copy(embedding, ndDiffused);
  4.   featuresList.addAll(featuresList);
  5.   features = featuresList.toArray(new Pruning.Feature[0]);
  6.   for (int i = features.length / 2; i < features.length; i++) {
  7.     features[i] = new Pruning.Feature("diffuse", features[i]);
  8.   }
  9.   for (int diffIteration = 0; diffIteration < diffusionIterations; diffIteration++) {
  10.     INDArray ndDiffusedTemp = Nd4j.create(embedding.shape());
  11.     nodeQueue.set(0);
  12.     final ArrayList<Future<?>> futures = new ArrayList<>();
  13.     for (int i = 0; i < concurrency; i++) {
  14.       futures.add(executorService.submit(new DiffusionTask(ndDiffused, ndDiffusedTemp)));
  15.     }
  16.     ParallelUtil.awaitTermination(futures);
  17.     ndDiffused = ndDiffusedTemp;
  18.   }
  19.   embedding = Nd4j.concat(1, embedding, ndDiffused);
  20. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. /**
  2.  * Append the given
  3.  * array with the specified value size
  4.  * along a particular axis
  5.  * @param arr the array to append to
  6.  * @param padAmount the pad amount of the array to be returned
  7.  * @param val the value to append
  8.  * @param axis the axis to append to
  9.  * @return the newly created array
  10.  */
  11. public static INDArray append(INDArray arr, int padAmount, double val, int axis) {
  12.   if (padAmount == 0)
  13.     return arr;
  14.   int[] paShape = ArrayUtil.copy(arr.shape());
  15.   if (axis < 0)
  16.     axis = axis + arr.shape().length;
  17.   paShape[axis] = padAmount;
  18.   INDArray concatArray = Nd4j.valueArrayOf(paShape, val);
  19.   return Nd4j.concat(axis, arr, concatArray);
  20. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. /**
  2.  * Append the given
  3.  * array with the specified value size
  4.  * along a particular axis
  5.  * @param arr the array to append to
  6.  * @param padAmount the pad amount of the array to be returned
  7.  * @param val the value to append
  8.  * @param axis the axis to append to
  9.  * @return the newly created array
  10.  */
  11. public static INDArray prepend(INDArray arr, int padAmount, double val, int axis) {
  12.   if (padAmount == 0)
  13.     return arr;
  14.   int[] paShape = ArrayUtil.copy(arr.shape());
  15.   if (axis < 0)
  16.     axis = axis + arr.shape().length;
  17.   paShape[axis] = padAmount;
  18.   INDArray concatArr = Nd4j.valueArrayOf(paShape, val);
  19.   return Nd4j.concat(axis, concatArr, arr);
  20. }

代码示例来源：origin: improbable-research/keanu

  1. /**
  2.  * @param dimension the dimension along which the tensors will be joined
  3.  * @param toConcat  an array of IntegerTensor
  4.  * @return  an IntegerTensor with toConcat joined along existing dimension
  5.  * <p>
  6.  * e.g. A, B, C = IntegerTensor.ones(4, 2)
  7.  * <p>
  8.  * IntegerTensor.concat(0, A, B, C) gives IntegerTensor.ones(12, 2)
  9.  */
  10. static IntegerTensor concat(int dimension, IntegerTensor... toConcat) {
  11.   INDArray[] concatAsINDArray = new INDArray[toConcat.length];
  12.   for (int i = 0; i < toConcat.length; i++) {
  13.     concatAsINDArray[i] = Nd4jIntegerTensor.unsafeGetNd4J(toConcat[i]).dup();
  14.     if (concatAsINDArray[i].shape().length == 0) {
  15.       concatAsINDArray[i] = concatAsINDArray[i].reshape(1);
  16.     }
  17.   }
  18.   INDArray concat = Nd4j.concat(dimension, concatAsINDArray);
  19.   return new Nd4jIntegerTensor(concat);
  20. }

代码示例来源：origin: improbable-research/keanu

  1. /**
  2.  * @param dimension the dimension along which the tensors will be joined
  3.  * @param toConcat  an array of DoubleTensor
  4.  * @return  a DoubleTensor with toConcat joined along an existing dimension
  5.  * <p>
  6.  * e.g. A, B, C = DoubleTensor.ones(4, 2)
  7.  * <p>
  8.  * DoubleTensor.concat(0, A, B, C) gives DoubleTensor.ones(12, 2)
  9.  */
  10. static DoubleTensor concat(int dimension, DoubleTensor... toConcat) {
  11.   INDArray[] concatAsINDArray = new INDArray[toConcat.length];
  12.   for (int i = 0; i < toConcat.length; i++) {
  13.     concatAsINDArray[i] = Nd4jDoubleTensor.unsafeGetNd4J(toConcat[i]).dup();
  14.     if (concatAsINDArray[i].shape().length == 0) {
  15.       concatAsINDArray[i] = concatAsINDArray[i].reshape(1);
  16.     }
  17.   }
  18.   INDArray concat = Nd4j.concat(dimension, concatAsINDArray);
  19.   return new Nd4jDoubleTensor(concat);
  20. }

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